What Can Machine Learning Contribute to Empathy in Design? How to Build a Journey Map Using Big Data and Text Sentiment Analysis

Sarah PagliaccioPrincipal, User Experience DesignerBlack Pepper

What can machine learning contribute to empathy in design? How to build a journey map using big data and text sentiment analysis.

Art and design are meant to reflect the world around us, show empathy for those we design for, and reflect the emotional state of our customers and target users. But how are we meant to empathize with situations that are unfamiliar or out of context? What happens when we over-empathize and project our own emotional states on our customers’ experiences? That’s where machine learning comes in. With enough input, we can use machine learning tools, specifically text sentiment analysis, to provide an objective score of our users’ emotional experiences. By feeding transcripts of customer interviews into a computer, we can remove our own subjectivity from our analysis and form a holistic picture of others’ needs and wants.

These sentiment scores can turn words into pictures, emotions into graphs, expanding our understanding of design goals and tasks.

Using Shakespeare’s A Midsummer Night’s Dream as a case study, we will talk through the emotional journey, i.e., the customer journey map, of major characters in the play using text sentiment analysis. A discussion of how these techniques can be applied to consumer application and website design will follow.

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